Volumetric 3D stitching of optical coherence tomography volumes

Optical coherence tomography (OCT) is a noninvasive medical imaging modality, which provides highresolution transectional images of biological tissue. However, its potential is limited due to a relatively small field of view. To overcome this drawback, we describe a scheme for fully automated stitch...

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Main Authors: Laves Max-Heinrich, Kahrs Lüder A., Ortmaier Tobias
Format: Article
Language:English
Published: De Gruyter 2018-09-01
Series:Current Directions in Biomedical Engineering
Subjects:
Online Access:https://doi.org/10.1515/cdbme-2018-0079
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spelling doaj-791af2fb10fb49cd82622dde3a05bf482021-09-06T19:19:26ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042018-09-014132733010.1515/cdbme-2018-0079cdbme-2018-0079Volumetric 3D stitching of optical coherence tomography volumesLaves Max-Heinrich0Kahrs Lüder A.1Ortmaier Tobias2Institute of Mechatronic Systems, Appelstr. 11A, 30167Hannover, GermanyInstitute of Mechatronic Systems, Appelstr. 11A, 30167Hannover, GermanyInstitute of Mechatronic Systems, Appelstr. 11A, 30167Hannover, GermanyOptical coherence tomography (OCT) is a noninvasive medical imaging modality, which provides highresolution transectional images of biological tissue. However, its potential is limited due to a relatively small field of view. To overcome this drawback, we describe a scheme for fully automated stitching of multiple 3D OCT volumes for panoramic imaging. The voxel displacements between two adjacent images are calculated by extending the Lucas-Kanade optical flow a lgorithm to dense volumetric images. A RANSAC robust estimator is used to obtain rigid transformations out of the resulting flow v ectors. T he i mages a re t ransformed into the same coordinate frame and overlapping areas are blended. The accuracy of the proposed stitching scheme is evaluated on two datasets of 7 and 4 OCT volumes, respectively. By placing the specimens on a high-accuracy motorized translational stage, ground truth transformations are available. This results in a mean translational error between two adjacent volumes of 16.6 ± 0.8 μm (2.8 ± 0.13 voxels). To the author’s knowledge, this is the first reported stitching of multiple 3D OCT volumes by using dense voxel information in the registration process. The achieved results are sufficient for providing high accuracy OCT panoramic images. Combined with a recently available high-speed 4D OCT, our method enables interactive stitching of hand-guided acquisitions.https://doi.org/10.1515/cdbme-2018-0079medical imagingimage processingregistrationpanoramic imagingmosaicingoptical flow
collection DOAJ
language English
format Article
sources DOAJ
author Laves Max-Heinrich
Kahrs Lüder A.
Ortmaier Tobias
spellingShingle Laves Max-Heinrich
Kahrs Lüder A.
Ortmaier Tobias
Volumetric 3D stitching of optical coherence tomography volumes
Current Directions in Biomedical Engineering
medical imaging
image processing
registration
panoramic imaging
mosaicing
optical flow
author_facet Laves Max-Heinrich
Kahrs Lüder A.
Ortmaier Tobias
author_sort Laves Max-Heinrich
title Volumetric 3D stitching of optical coherence tomography volumes
title_short Volumetric 3D stitching of optical coherence tomography volumes
title_full Volumetric 3D stitching of optical coherence tomography volumes
title_fullStr Volumetric 3D stitching of optical coherence tomography volumes
title_full_unstemmed Volumetric 3D stitching of optical coherence tomography volumes
title_sort volumetric 3d stitching of optical coherence tomography volumes
publisher De Gruyter
series Current Directions in Biomedical Engineering
issn 2364-5504
publishDate 2018-09-01
description Optical coherence tomography (OCT) is a noninvasive medical imaging modality, which provides highresolution transectional images of biological tissue. However, its potential is limited due to a relatively small field of view. To overcome this drawback, we describe a scheme for fully automated stitching of multiple 3D OCT volumes for panoramic imaging. The voxel displacements between two adjacent images are calculated by extending the Lucas-Kanade optical flow a lgorithm to dense volumetric images. A RANSAC robust estimator is used to obtain rigid transformations out of the resulting flow v ectors. T he i mages a re t ransformed into the same coordinate frame and overlapping areas are blended. The accuracy of the proposed stitching scheme is evaluated on two datasets of 7 and 4 OCT volumes, respectively. By placing the specimens on a high-accuracy motorized translational stage, ground truth transformations are available. This results in a mean translational error between two adjacent volumes of 16.6 ± 0.8 μm (2.8 ± 0.13 voxels). To the author’s knowledge, this is the first reported stitching of multiple 3D OCT volumes by using dense voxel information in the registration process. The achieved results are sufficient for providing high accuracy OCT panoramic images. Combined with a recently available high-speed 4D OCT, our method enables interactive stitching of hand-guided acquisitions.
topic medical imaging
image processing
registration
panoramic imaging
mosaicing
optical flow
url https://doi.org/10.1515/cdbme-2018-0079
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AT kahrsludera volumetric3dstitchingofopticalcoherencetomographyvolumes
AT ortmaiertobias volumetric3dstitchingofopticalcoherencetomographyvolumes
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